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• Trials in RA: choosing the right outcome measure
  Duncan Porter
  Published on: 9 May 2008

• Published on: 9 May 2008

  Trials in RA: choosing the right outcome measure

  • Duncan Porter, Consultant Rheumatologist

  Dear Editor,

  Felson et al make a good case for choosing continuous, rather than dichotomous, variables as the primary outcome measures in randomised controlled trials in rheumatoid arthritis but outcome measure also need to be meaningful to the clinical community. In TICORA we chose two ‘co-primary’ end-points: firstly, we employed the mean change in DAS because this was the most sensitive outcome measure available at...

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  Dear Editor,

  Felson et al make a good case for choosing continuous, rather than dichotomous, variables as the primary outcome measures in randomised controlled trials in rheumatoid arthritis but outcome measure also need to be meaningful to the clinical community. In TICORA we chose two ‘co-primary’ end-points: firstly, we employed the mean change in DAS because this was the most sensitive outcome measure available at the time; we also used the achievement of a “good” response according to EULAR criteria because we believed that differences in response rates would be more readily understood. Interestingly, our understanding of the clinical relevance of the outcome measures has been borne out: the results of the trial are (almost) never quoted as showing that the mean fall in DAS was 1.6 units (95% CI, 1.1 to 2.1) greater in the intensive arm - commentators almost invariably refer instead to the higher response rates. Consequently, I would urge some caution on the clinical trials community not to rely on sensitive (but intuitively difficult to understand) outcome measures to the exclusion of response rates. This is acknowledged by Felson et al when they recognise that such measures can be secondary outcome measures but it may still be important that some trials (depending on their purpose) are large enough to be able to detect clinically significant differences in response rates.

  There has been a growing tendency for the therapeutic research agenda to become dominated by the pharmaceutical industry in their pursuit of marketing authorisation for new products. Felson et al point out that using sensitive outcome measures may avoid the need for ‘mega-trials’. Importantly, smaller and cheaper trials will help to safeguard the role of independent, investigator-initiated research which has been so fruitful in recent years. The second impact of designing smaller trials is, however, less helpful because it demands a degree of expertise in interpreting trial results. TICORA was a small trial, and so the magnitude of the benefits could not be assessed with any precision. The odds ratio for an ACR 70 response with intensive therapy was 11, but the 95% confidence interval for that odds ratio was 4.5 to 27. Rather than describe the trial as an ‘outlier’ the authors should perhaps have commented that the results should be interpreted carefully in light of the confidence intervals described in the paper.

  I would add one further observation about dichotomous variables when the cohort average is close to a cut-off point. After 12 months, 44% of the TICORA intensive group were in DAS remission (data on file). At this point, the median DAS in the intensive group was 1.7, just above the cut-off for DAS remission. At 18 months, the median DAS had fallen to 1.3, just below the cut-off. This modest improvement in DAS was probably of limited clinical significance yet it resulted in a substantial increase in the remission rate (from 44% to 65%).

  In conclusion, I would endorse the authors’ recommendation to use continuous measures of disease activity as primary outcome measures. This should ensure that smaller trials will be possible, and in turn this may help to safeguard the role of independent investigator-initiated research. However, trialists should continue to make sure that their measures are comprehensible and relevant, and the clinical community must be careful to interpret the results of trials thoughtfully.

  References

  1. D Felson, B Zhang and J Siegel. Trials in rheumatoid arthritis: choosing the right outcome measure when minimal disease is achievable. Ann Rheum Dis 2008;57:580-582.

  2. C Grigor, H Capell, A Stirling et al. Effect of a treatment strategy of tight control for rheumatoid arthritis (the TICORA study): a single-blind randomised controlled trial. Lancet 2004;364:263-269.

  3. D Porter. Targeting persistent disease activity in early RA: a commentary on the TICORA trial. International Journal of Advances in Rheumatology. 2005;3:2-6.

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  Conflict of Interest:
  None declared.

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